// Bayesian network 
network "InternalNetwork" { //5 variables and 5 probability distributions
}
variable  "Difficulty" { //2 values
	type discrete[2] {  "true"  "false" };
	property "position = (147, 113)" ;
}
variable  "Grade" { //2 values
	type discrete[2] {  "true"  "false" };
	property "position = (232, 219)" ;
}
variable  "SAT" { //2 values
	type discrete[2] {  "true"  "false" };
	property "position = (374, 226)" ;
}
variable  "Intelligence" { //2 values
	type discrete[2] {  "true"  "false" };
	property "position = (320, 115)" ;
}
variable  "Letter" { //2 values
	type discrete[2] {  "true"  "false" };
	property "position = (215, 346)" ;
}
probability (  "Difficulty" ) { //1 variable(s) and 2 values
	table 
		0.9	// p(true | evidence )
		0.1; 	// p(false | evidence );
}
probability (  "Grade"  "Difficulty"  "Intelligence" ) { //3 variable(s) and 8 values
	table 
		 0.7 0.01 0.99 0.5 0.3 0.99 0.01 0.5;
}
probability (  "SAT"  "Intelligence" ) { //2 variable(s) and 4 values
	table 
		 0.8 0.05 0.2 0.95;
}
probability (  "Intelligence" ) { //1 variable(s) and 2 values
	table 
		0.8	// p(true | evidence )
		0.2; 	// p(false | evidence );
}
probability (  "Letter"  "Grade" ) { //2 variable(s) and 4 values
	table 
		 0.8 0.1 0.2 0.9;
}